Recognizing and tracking humans and vehicles using radar

Abstract

Dynamic obstacles like vehicles and animals can be distinguished from humans using their radar micro-Doppler signature. This allows customizing the robotic path algorithm to avoid highly sensitive and unpredictable obstacles like humans and rapidly moving obstacles like vehicles. We demonstrate the extraction of stride rate and other information associated with gait for enhanced person recognition from radar data. We describe the radar sensors used for the measurements, the algorithms used for the detection, tracking, and classification of people and vehicles, as well as describe some of the features that can be extracted. These features can serve as rudimentary identifying information in a scene with multiple subjects. We measure human subjects in indoor and outdoor clutter backgrounds for identification and gather ground truth using video to validate the radar data.